TY - JOUR
T1 - Simulation of evapotranspiration and yield of maize
T2 - An Inter-comparison among 41 maize models
AU - Kimball, Bruce A.
AU - Thorp, Kelly R.
AU - Boote, Kenneth J.
AU - Stockle, Claudio
AU - Suyker, Andrew E.
AU - Evett, Steven R.
AU - Brauer, David K.
AU - Coyle, Gwen G.
AU - Copeland, Karen S.
AU - Marek, Gary W.
AU - Colaizzi, Paul D.
AU - Acutis, Marco
AU - Alimagham, Seyyedmajid
AU - Archontoulis, Sotirios
AU - Babacar, Faye
AU - Barcza, Zoltán
AU - Basso, Bruno
AU - Bertuzzi, Patrick
AU - Constantin, Julie
AU - De Antoni Migliorati, Massimiliano
AU - Dumont, Benjamin
AU - Durand, Jean Louis
AU - Fodor, Nándor
AU - Gaiser, Thomas
AU - Garofalo, Pasquale
AU - Gayler, Sebastian
AU - Giglio, Luisa
AU - Grant, Robert
AU - Guan, Kaiyu
AU - Hoogenboom, Gerrit
AU - Jiang, Qianjing
AU - Kim, Soo Hyung
AU - Kisekka, Isaya
AU - Lizaso, Jon
AU - Masia, Sara
AU - Meng, Huimin
AU - Mereu, Valentina
AU - Mukhtar, Ahmed
AU - Perego, Alessia
AU - Peng, Bin
AU - Priesack, Eckart
AU - Qi, Zhiming
AU - Shelia, Vakhtang
AU - Snyder, Richard
AU - Soltani, Afshin
AU - Spano, Donatella
AU - Srivastava, Amit
AU - Thomson, Aimee
AU - Timlin, Dennis
AU - Trabucco, Antonio
AU - Webber, Heidi
AU - Weber, Tobias
AU - Willaume, Magali
AU - Williams, Karina
AU - van der Laan, Michael
AU - Ventrella, Domenico
AU - Viswanathan, Michelle
AU - Xu, Xu
AU - Zhou, Wang
N1 - We appreciate access to the comprehensive dataset from Mead, Nebraska, USA, which was collected by the following scientists: Shashi B. Verma, Achim Dobermann, Kenneth G. Cassman, Daniel T. Walters, Johannes M. Knops, Timothy J. Arkebauer, George G. Burba, Brigid Amos, Haishum Yang, Daniel Ginting, Kenneth G. Hubbard, Anatoly A. Gitelson, and Elizabeth A. Walter-Shea. The dataset was collected with support from the DOE-Office of Science (BER: Grant Nos. DE-FG03–00ER62996 and DE-FG02–03ER63639 ), DOE-EPSCoR (Grant No. DE-FG02–00ER45827 ), and the Cooperative State Research, Education, and Extension Service, US Department of Agriculture (Agreement No. 2001–38700–11092 ). Funding was also provided by the National Multidisciplinary Laboratory for Climate Change , RRF-2.3.1–21–2022–00014 project. Additional support was provided by grant " Advanced research supporting the forestry and wood-processing sector´s adaptation to global change and the 4th industrial revolution ", No. CZ.02.1.01/0.0/0.0/16_019/0000803 financed by OP RDE. KW was supported by the Met Office Hadley centre Climate Programme funded by BEIS .
We appreciate access to the comprehensive dataset from Mead, Nebraska, USA, which was collected by the following scientists: Shashi B. Verma, Achim Dobermann, Kenneth G. Cassman, Daniel T. Walters, Johannes M. Knops, Timothy J. Arkebauer, George G. Burba, Brigid Amos, Haishum Yang, Daniel Ginting, Kenneth G. Hubbard, Anatoly A. Gitelson, and Elizabeth A. Walter-Shea. The dataset was collected with support from the DOE-Office of Science (BER: Grant Nos. DE-FG03–00ER62996 and DE-FG02–03ER63639), DOE-EPSCoR (Grant No. DE-FG02–00ER45827), and the Cooperative State Research, Education, and Extension Service, US Department of Agriculture (Agreement No. 2001–38700–11092). Funding was also provided by the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1–21–2022–00014 project. Additional support was provided by grant "Advanced research supporting the forestry and wood-processing sector´s adaptation to global change and the 4th industrial revolution", No. CZ.02.1.01/0.0/0.0/16_019/0000803 financed by OP RDE. KW was supported by the Met Office Hadley centre Climate Programme funded by BEIS.
PY - 2023/4/15
Y1 - 2023/4/15
N2 - Accurate simulation of crop water use (evapotranspiration, ET) can help crop growth models to assess the likely effects of climate change on future crop productivity, as well as being an aid for irrigation scheduling for today's growers. To determine how well maize (Zea mays L.) growth models can simulate ET, an initial inter-comparison study was conducted in 2019 under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). Herein, we present results of a second inter-comparison study of 41 maize models that was conducted using more comprehensive datasets from two additional sites - Mead, Nebraska, USA and Bushland, Texas, USA. There were 20 treatment-years with varying irrigation levels over multiple seasons at both sites. ET was measured using eddy covariance at Mead and using large weighing lysimeters at Bushland. A wide range in ET rates was simulated among the models, yet several generally were able to simulate ET rates adequately. The ensemble median values were generally close to the observations, but a few of the models sometimes performed better than the median. Many of the models that did well at simulating ET for the Mead site did poorly for drier, windy days at the Bushland site, suggesting they need to improve how they handle humidity and wind. Additional variability came from the approaches used to simulate soil water evaporation. Fortunately, several models were identified that did well at simulating soil water evaporation, canopy transpiration, biomass accumulation, and grain yield. These models were older and have been widely used, which suggests that a larger number of users have tested these models over a wider range of conditions leading to their improvement. These revelations of the better approaches are leading to model improvements and more accurate simulations of ET.
AB - Accurate simulation of crop water use (evapotranspiration, ET) can help crop growth models to assess the likely effects of climate change on future crop productivity, as well as being an aid for irrigation scheduling for today's growers. To determine how well maize (Zea mays L.) growth models can simulate ET, an initial inter-comparison study was conducted in 2019 under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project). Herein, we present results of a second inter-comparison study of 41 maize models that was conducted using more comprehensive datasets from two additional sites - Mead, Nebraska, USA and Bushland, Texas, USA. There were 20 treatment-years with varying irrigation levels over multiple seasons at both sites. ET was measured using eddy covariance at Mead and using large weighing lysimeters at Bushland. A wide range in ET rates was simulated among the models, yet several generally were able to simulate ET rates adequately. The ensemble median values were generally close to the observations, but a few of the models sometimes performed better than the median. Many of the models that did well at simulating ET for the Mead site did poorly for drier, windy days at the Bushland site, suggesting they need to improve how they handle humidity and wind. Additional variability came from the approaches used to simulate soil water evaporation. Fortunately, several models were identified that did well at simulating soil water evaporation, canopy transpiration, biomass accumulation, and grain yield. These models were older and have been widely used, which suggests that a larger number of users have tested these models over a wider range of conditions leading to their improvement. These revelations of the better approaches are leading to model improvements and more accurate simulations of ET.
KW - Crop models
KW - Evapotranspiration
KW - Maize
KW - Simulation
KW - Water use
KW - Yield
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U2 - 10.1016/j.agrformet.2023.109396
DO - 10.1016/j.agrformet.2023.109396
M3 - Article
AN - SCOPUS:85149752687
SN - 0168-1923
VL - 333
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
M1 - 109396
ER -